The Rise of Artificial Unintelligence
Computers may one day be able to reason exactly as humans do, but will they ever be as dumb? I had always thought that was impossible. Now, however, I’m not so sure...

Automatic tagging using deep convolutional neural networks
We present a content-based automatic music tagging algorithm using fully convolutional neural networks (FCNs). The experiments show that mel-spectrogram is an effective time-frequency representation for automatic tagging and that more complex models benefit from more training data...

Goods: organizing Google’s datasetsYou can (try and) build a data cathedral. Or you can build a data bazaar. By data cathedral I’m referring to a centralised Enterprise Data Management solution that everyone in the company buys into and pays homage to, making a pilgrimage to the EDM every time they want to publish or retrieve a dataset. A data bazaar on the other hand abandons premeditated centralised control...

Building a Data Pipeline with AirflowIn this blog post I'll setup a data pipeline that takes currency exchange rates, stores them in PostgreSQL and then caches the latest exchange rates in Redis...

Modeling Madly: Machine learning at hackathonsThese past two hackathons I’ve taken on some slightly different challenges than people usually go after in a hackathon: developing new machine learning models. While I‘ve been working on data science and machine learning systems for a while, I’ve found that trying to do so under extreme constraints can be a distinctly different experience...

Image Completion with Deep Learning in TensorFlowThis paper shows how to use deep learning for image completion with a DCGAN. This blog post is meant for a general technical audience with some deeper portions for people with a machine learning background...

Design Better Data TablesPoor tables. Where did they go wrong? After being the bread and butter of the web for most of its early history, tables were cast aside by many designers for newer, trendier layouts. But while they might be making fewer appearances on the web these days, data tables still collect and organize much of the information we interact with on a day-to-day basis...

Jobs

The StreetEasy Economic Research team is looking for an outstanding Data Scientist to join us. You will be responsible for deriving fascinating insights on the New York housing market from terabytes of StreetEasy market and usage data. This role will require a candidate who can apply a breadth of tools, data sources and analytical techniques to answer a wide range of high level questions and present the insights in a concise and effective manner. You'll work in an informal, collaborative atmosphere with a team of smart self-starters like yourself...

Training & Resources

Grouping in PandasGrouping data is an integral part of many data analysis projects. The functionality for grouping in pandas is vast, but can be tough to grasp initially. Have no fear...we will get through a short introduction together using some data from NYC's beloved bike share program, Citi Bike...